What Is LLM Poisoning?
A joint study from Anthropic, the UK AI Security Institute and the Alan Turing Institute found that just 250 malicious documents can slip a “backdoor” into any large language model—whether it’s a lean 600 M-parameter model or a hefty 13 B one trained on 20× more data. In short, a tiny batch of poisoned examples is surprisingly all it takes to compromise an LLM’s integrity.
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